Evidence map›Paper›PMID 34607011›Full record

ArticleAnnals of epidemiology2021

Mortality following workplace injury: Quantitative bias analysis.

Andrew Busey, Abay Asfaw, Katie M Applebaum, Paul K O'Leary, Yorghos Tripodis, Matthew P Fox, Andrew C Stokes, Leslie I Boden

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Andrew BuseyNERA Economic Consulting, Boston, MA, USA. Electronic address: andrew.busey@nera.com.
Abay AsfawCenters for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC, USA. Electronic address: hqp0@cdc.gov.
Katie M ApplebaumDepartment of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA. Electronic address: kapplebaum@email.gwu.edu.
Paul K O'LearyU.S. Social Security Administration, Office of Retirement and Disability Policy, Washington, DC, USA. Electronic address: Paul.Oleary@ssa.gov.
Yorghos TripodisDepartment of Biostatistics, Boston University School of Public Health, 715 Albany St., Boston, MA 02118, USA. Electronic address: yorghos@bu.edu.
Matthew P FoxDepartments of Epidemiology and Global Health, Boston University School of Public Health, 715 Albany St., Boston, MA 02118, USA. Electronic address: mfox@bu.edu.
Andrew C StokesDepartment of Global Health, Boston University School of Public Health, 715 Albany St., Boston, MA 02118, USA. Electronic address: acstokes@bu.edu.
Leslie I BodenDepartment of Environmental Health, Boston University School of Public Health, 715 Albany St., Boston, MA 02118, USA. Electronic address: lboden@bu.edu.

Funding

All-Cause and Cause-Specific Mortality Resulting from Non-Fatal Occupational InjuriesR01OH011511 · OH · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BODEN, LESLIE I. · 2018 to 2021
$1.5M
Mortality Consequences of Non-Fatal Occupational InjuriesR21OH010555 · OH · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BODEN, LESLIE I. · 2014 to 2015
$450k
Intramural CDC HHS CC999999NIOSH CDC HHS R01 OH011511NIOSH CDC HHS R21 OH010555
6 · The paper itself

Abstract

purposeRecent studies have shown increased all-cause mortality among workers following disabling workplace injury. These studies did not account for 2 potentially important confounders, smoking and obesity. We estimated injury-related mortality accounting for these factors.

methodsWe followed workers receiving New Mexico workers' compensation benefits (1994-2000) through 2013. Using data from the Panel Study of Income Dynamics, we derived the joint distribution of smoking status and obesity for workers with and without lost-time injuries. We conducted a quantitative bias analysis (QBA) to determine the adjusted relationship of injury and mortality.

resultsWe observed hazard ratios after adjusting for smoking and obesity of 1.13 for women (95% simulation interval (SI) 0.97 to 1.31) and 1.12 for men (95% SI 1.00 to 1.27). The estimated fully adjusted excess hazard was about half the estimates not adjusted for these factors.

conclusionsUsing QBA to adjust for smoking and obesity reduced the estimated mortality hazard from lost-time injuries and widened the simulation interval. The adjusted estimate still showed more than a 10 percent increase for both women and men. The change in estimates reveals the importance of accounting for these confounders. Of course, the results depend on the methods and assumptions used.

Indexed as

Workers' CompensationWorkplaceBiasFemaleHumansIncomeMaleProportional Hazards ModelsConfoundingEpidemiological biasExcess mortalityOccupational SafetyQuantitative bias analysis

Identifiers

PMID34607011
PMCPMC10026009

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.